With every passing day, the world becomes more digitally interconnected. The Internet of Things (IoT) continues to facilitate this interconnection of devices. In fact, estimates indicate that the number of connected devices is expected to grow to anywhere from 20 to 50 billion by the end of the decade. Connected devices can range from stand-alone, wireless sensors such as accelerometers, to wearable devices, vehicles, power plants, buildings, and more. Typically, interconnected devices are embedded with electronics and software, including connectivity means, in order to collect and/or exchange data with other devices.
Notably, wireless sensors are increasingly being embedded in just about any object or surface, in order to collect data and generate “smarter” people and things. For instance, sensors are often embedded in machines, walls, wearable devices, clothing, and even in and on people's bodies. These sensors are configured to sample data relating to their surroundings and/or the person or object on which they are provided. The sensors can then transmit the sampled data to other computing devices for further analysis and storage. Thus, in order to maximize the amount of data that can be gathered, sensors are optimized to be as power- and throughput-efficient as possible. To this end, low-power radios and technologies such as Bluetooth Low Energy (BLE), ZigBee, Z-Wave, and others have been developed to reduce the amount of power consumed by devices during the data exchange process. In addition, backscatter is a communications technique that shifts power burdens to the reader side as opposed to the tag (e.g., sensor) side. This is achieved, for example, by configuring the reader to generate a carrier signal that includes power to be delivered to the tag. As a result, the tag can benefit from less hardware complexity, enabling the creation of less expensive and smaller tags and sensors. This, in turn, allows more sensors to be deployed, and more data to be collected.
One drawback of existing backscattering techniques is that they are not designed to provide the same power-consumption benefits when dealing with concurrent transmission from heterogeneous sensors a variety of sensors having different sampling and transmission rates. For example, traditional backscattering techniques are optimized for specific hardware configurations. By requiring all nodes to transmit data at a particular rate, existing backscattering techniques either underutilize the transmission rates of more efficient tags or cause less efficient tags to employ other hardware and logic (e.g., clock, buffer) to transmit data at the selected rate.
Thus, there is a need for a backscatter protocol that enables a reader to decode transmitted asynchronous and concurrent signals from heterogeneous tags. There is also a need for tags to be able to transmit at their respectively optimal rates. There is further a need to minimize the hardware and logic at the tags, in order to reduce the power consumption and size of the tags.